similar to: Aggregate issues with subset

Hello, I am trying to plot multiple histograms with the same scales, etc into one plot. The commands below produce a 3 page PDF with each histogram occupying the upper right quadrant. And use slightly different scales on the X and Y axes. > s21 <- dat[dat$sc_recov=="21",] > s21.ED <- subset(s21, select=(bbED)) > s31 <- all[all$sc_recov=="31",] > s31.ED

The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle. > set.seed(143) > m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T)) > m A B C D 1 E I 1 NA 2 A C NA NA 3 D I NA 3 4 C I

Hi, R-users, If I have a data frame like this: >x<-data.frame(g=c("g1","g2","g1","g1","g2"),v=c(1,7,3,2,8)) g v 1 g1 1 2 g2 7 3 g1 3 4 g1 2 5 g2 8 It contains two groups, g1 and g2. Now for each group I want the max v: > aggregate(x$v,list(g=x$g),max) g x 1 g1 3 2 g2 8 Beautiful. But what if I want to keep the row index of (g1

Hi the list, As it is say in its doc, the aggregate function remove empty subsets. Is it possible to NOT remove empty subset ? --- 8< ------- m <- matrix(1:12,4) part <- factor(c("A","B","A","B"),levels=c("A","B","C")) aggregate(m,list(part),mean) ### I get: # Group.1 V1 V2 V3 # 1 A 2 6 10 # 2 B 3 7

Dear all, I have a data frame of three columns, which I have sorted by Latitude as follows: > test2[60:80,] Latitude Longitude Sim_1986 61948 85.25 -29.25 2.175345 61957 85.25 -28.75 8.750486 61967 85.25 -28.25 33.569305 61977 85.25 -27.75 23.702572 61988 85.25 -27.25 26.488602 62000 85.25 -26.75 23.915724 62012 85.25 -26.25 25.055082 62027

Hi everyone. I have these data : myData = data.frame(Name = c('a', 'a', 'b', 'b'), length = c(1,2,3,4), type = c('x','x','y','z')) which gives me: Name length type 1 a 1 x 2 a 2 x 3 b 3 y 4 b 4 z I would group (mean) this DF using 'Name' as grouping factor. However, I have a

Hi, I am using aggregate() to add up groups of data according to year and month. It seems that the function aggregate() automatically sorts the levels of factors of the grouping elements, even if the order of the levels of factors is supplied. I am wondering if this is a bug, or if I missed something important. Below is an example that shows what I mean. Does anyone know if this is just the way

I would like to reformat this data frame into something that I can produce some descriptive statistics. I have been playing around with the reshape package and maybe this is not the best way to proceed. I would like to use RiverMile and constituent as the grouping variables to get the summary statistics: 198a 198b mean mean sd sd ... ... etc. for all of these. I have tried

Hi, When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables. So for example in this data-frame: data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5))) aggregate(data,

Dear r-help reader, I have some problems with the aggregate function. My datframe looks like >frame Day Time V1 V2 1 M 0 3 NA 2 M 0 4 NA 3 M 0 5 2 4 M 1 NA 4 5 M 1 10 6 6 T 0 4 45 7 T 1 4 3 8 T 1 3 2 9 T 1 6 1 I used the aggegate function to obtain the mean in V1 and V2 over the grouping variable Time and Day

Hi, I have a data.frame which I want to aggregate. There are some grouping variables and some continuous variables for which I would like to have the mean. However there are also some factor-variables in the data-frame that are not grouping variables and I actually would like to aggregate these variables with the unique() function. Is that possible with the standard aggregate-function? If I

I have a data frame with two columns, a factor and a numeric. I want to create data frame with the factor, its frequency and the median of the numeric column > head(motifList) events score 1 aeijm -0.25000000 2 begjm -0.25000000 3 afgjm -0.25000000 4 afhjm -0.25000000 5 aeijm -0.25000000 6 aehjm 0.08333333 To get the frequency table of events: > motifTable <-

Dear expeRts, The question is rather simple: Why does aggregate (or similarly tapply()) not keep the order of the grouping variable(s)? Here is an example: x <- data.frame(group = rep(LETTERS[1:2], each=10), year = rep(rep(2001:2005, each=2), 2), value = rep(1:10, each=2)) ## => sorted according to group, then year aggregate(value ~ group + year, data=x,

Dear all, I am trying to apply the aggregate() function to calculate correlations for subsets of a dataframe. My argument x is supposed to consist of 2 numerical vectors, which represent x and y for the cor() function. The following error results when calling the aggregate function: Error in FUN(X[[1L]], ...) : supply both 'x' and 'y' or a matrix-like 'x'. I think the

hi all - i'm just wondering what sort of code people write to essentially performa an aggregate call, but with different functions being applied to the various columns. for example, if i have a data frame x and would like to marginalize by a factor f for the rows, but apply mean() to col1 and median() to col2. if i wanted to apply mean() to both columns, i would call: aggregate(x, list(f),

Hi R users and developers on debian platforms. I compile the R version 2.8.1 Patched (2009-03-18 r48193) on my UBUNTU linux distribution. But when I ask for the aggregate example it fails. What am I missing? example(aggregate) aggrgt> ## Compute the averages for the variables in 'state.x77',grouped aggrgt> ## according to the region (Northeast, South, North Central,West) that

Hello list, I'm new to this list, so please forgive my ignorance. I have searched R-help for some hints into what might be my problem, but I truly have no idea where to go from here. I have an object of approximately 15,000 rows and 2 columns. There are many duplicates in the first column, all with different corresponding values in the second column. For example (2 is duplicated):

Hi R developers and debian users: Finally I found how to work with aggregate() function on the last patched version fo R. I you use this command it fails: aggregate(state.x77, list(Region = state.region), mean) But if you modify it in this way, it works!: aggregate(state.x77, list(Region = state.region), function(x) mean(x) ) Is it necesary to change the example? What is changing in

Hi R developers and debian users: Finally I found how to work with aggregate() function on the last patched version fo R. I you use this command it fails: aggregate(state.x77, list(Region = state.region), mean) But if you modify it in this way, it works!: aggregate(state.x77, list(Region = state.region), function(x) mean(x) ) Is it necesary to change the example? What is changing in

All, I've been using aggregate() to compute means and standard deviations at time/treatment combinations for a longitudinal dataset, using na.rm = TRUE for missing data. This was working fine before, but now when I re-run some old code it isn't. I've backtracked my steps and can't seem to find out why it was working before but not now. In any event, below is a reproducible